Rapid optimization of drug combinations for the optimal angiostatic treatment of cancer
Rapid optimization of drug combinations for the optimal angiostatic treatment of cancer
复制标题
快速优化药物组合以实现癌症的最佳血管抑制治疗
DOI：
10.1007/s10456-015-9462-9
复制
发表时间：
2015-07-01
期刊：
影响因子：
9.8
通讯作者：
Nowak-Sliwinska, Patrycja
中科院分区：
文献类型：
--
作者：
Weiss, Andrea;Ding, Xianting;Nowak-Sliwinska, Patrycja
药物组合可以提高血管抑制性癌症治疗功效，并能够减少副作用和耐药性。由于可能性很高，联合用药并非微不足道。我们应用反馈系统控制（FSC）技术与基于群体的随机搜索算法，通过大的参数空间的九种血管抑制药物在四个浓度，以确定最佳的低剂量药物组合导航。这意味着内皮细胞活力的体外测试和基于算法的分析的迭代方法。最佳的协同药物组合，包含厄洛替尼，BEZ-235和RAPTA-C，在少量的迭代中达到。最终的药物组合显示增强的内皮细胞特异性和协同抑制增殖（p < 0.001），但不抑制内皮细胞的迁移，并迫使增加的内皮细胞数目经历凋亡（p < 0.01）。在两种临床前体内肿瘤模型中实现了这种药物组合的成功转化。与最佳单一药物浓度相比，使用减少的药物剂量协同地且显著地抑制肿瘤生长（分别为p < 0.05和p < 0.01）。在应用条件下，单一药物单一疗法在这些模型中没有活性或活性可忽略不计。我们认为，FSC可用于快速识别有效的，减少剂量，多药物组合治疗癌症和其他疾病。
Drug combinations can improve angiostatic cancer treatment efficacy and enable the reduction of side effects and drug resistance. Combining drugs is non-trivial due to the high number of possibilities. We applied a feedback system control (FSC) technique with a population-based stochastic search algorithm to navigate through the large parametric space of nine angiostatic drugs at four concentrations to identify optimal low-dose drug combinations. This implied an iterative approach of in vitro testing of endothelial cell viability and algorithm-based analysis. The optimal synergistic drug combination, containing erlotinib, BEZ-235 and RAPTA-C, was reached in a small number of iterations. Final drug combinations showed enhanced endothelial cell specificity and synergistically inhibited proliferation (p < 0.001), but not migration of endothelial cells, and forced enhanced numbers of endothelial cells to undergo apoptosis (p < 0.01). Successful translation of this drug combination was achieved in two preclinical in vivo tumor models. Tumor growth was inhibited synergistically and significantly (p < 0.05 and p < 0.01, respectively) using reduced drug doses as compared to optimal single-drug concentrations. At the applied conditions, single-drug monotherapies had no or negligible activity in these models. We suggest that FSC can be used for rapid identification of effective, reduced dose, multi-drug combinations for the treatment of cancer and other diseases.